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Group of services. The objective is to recover from most errors and exceptions without human intervention, if possible. Enabling online upgrades and versioning is the process of placing new services and/or policies into service, controlling the process around the upgrades made to services and/or policies, and controlling how services and/or policies are versioned. This is done by allowing the repository to track all services and policies under management, including the complete history of services and policies that have been created, tested, and deployed in either the on-premise or cloud computing based systems. As developers build new versions of services, or as policy designers design and build new policies, a mechanism must be in place to insure that updating services and policies will not break the existing system or systems. Runtime service governance is able to track any upgrades that are made, insuring that the applications, processes, and other services leveraging those services are made aware of the change; that alterations are made; and that testing is completed. Moreover, if issues are discovered, there should be a mechanism to return to the previous version of the service and/or policy. Besides the use of policies to control access to services, this is one of the most important functions of runtime governance. Service validation, as the name implies, is the feature of the governance technology that validates that the services are well formed and prepared to go into production. Service validation asks the question, Is this service valid to the policies and to its expected behavior when in production Auditing and logging means that the governance technology will track the execution of the services and the policies, including what they do, when they do it, and who they do it with. This allows those who manage the holistic architecture to analyze auditing and logging information to determine why problems occurred, or better yet, to prevent them. Auditing is required by many legal compliance standards, such as those imposed on public companies or those in regulated vertical markets such as health care. Governance Dos and Don"ts

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On other services are understood, from the highest level to the lowest. For instance, the service Rent a Car is made up of Reserve a Car, Pick Up Car, Drop off Car. However, the service Reserve a Car is made up of Identify Customer, Select Car, and Enter Reservation. You get the idea. In essence, we de ne the services as they exist in a hierarchy, from the highest to the lowest level, not forgetting to de ne the data that is bound to those services. For instance, let s go back to our candidate services for General Ledger: Update_Product may be decomposed to:

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Why is SOA and SOA using cloud computing so different that we need a different approach to testing Many of the same patterns around testing a distributed computing system, such as a SOA, are applicable here. We are not asking you to test much differently but only to consider a few new issues.

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There is not a set format or rules around what a data dictionary should consist of. A quick and dirty listing of the data is just ne. We just need to provide a base understanding of all the existing data to move to the next step in cataloging the data. The data catalog for this problem domain is the combination of all the data dictionaries into one common place, using one common approach and format. This the rst step in abstracting the data structures from their physical instances into a common listing of data assets that we will use to determine our to-be database solution, including any use of cloud computing resources that may a t once we are through this process. The data catalog (very much simpli ed) for our BMH problem domain may look like Table 5.1. This is just a raw listing of the data elements found in all of the data dictionaries, in this case three. However, you need to add some additional information, including Description Ownership Security parameters Integrity parameters Dependencies Again, there are no set rules for what should be contained in a data catalog, so you can create a data catalog that best meets your requirements. Moving on to the information model, it is a good idea to identify the common entities in this problem domain. In our BMH example, we have 1. Customer 2. Sales 3. Products That simple. It is also good to de ne the relationships, such as Customer buys Products, which creates Sales. Again, not complex. So, the to-be or target information model that we consider when building our SOA using cloud computing could be as follows: Customer Customer_Number Customer_Name Company_Name Customer_Address Customer_State Customer_Zip

Portant is that you recognize and understand the resources you have to work with to change your enterprise architecture by leveraging cloud computing. The next steps are about how to change your enterprise architecture to incorporate SOA using cloud computing. We look at how to approach your enterprise architecture by understanding what you have and how cloud computing and SOA may improve it.

To develop a new system, you must pay for development and you must design for peak loads, which results in excess capacity that often goes unused. The need to build in this excess capacity means that your investment in hardware and software will be underutilized most of the time. Cloud services should be less expensive because you pay only for what you use. If you are working with an existing system that is, trying to decide whether to wrap a legacy system as a service or to a cloud service the case is less compelling, because many of the in-house expenditures have already been made and amortized. You have to consider all of these points in your cloud-versus-host decision.